As a discrete spectrum correction method,the Fourier transform(FT) continuous zoom analysis method is widely used in vibration signal analysis,but little effort had been made on this method's anti-noise performance.It is widely believed that the analysis accuracy of the method can be substantially improved by increasing the zoom multiple,however,with the zoom multiple increases,the frequency estimation accuracy may decline sometimes in practices.Aiming at the problems above,this paper analyzes the sources of frequency estimation error when a harmonic signal mixed with and without noise is processed using the FT continuous zoom analysis.According to the characteristics that the local maximum of the zoom spectrum may be wrongly selected when the signal is corrupted with noise,the number of wrongly selected spectrum lines is deduced under different signal-to-noise ratio and local zoom multiple,and then the maximum frequency estimation error is given accordingly.The validity of the presented analysis is confirmed by simulations results.The frequency estimation accuracy of this method will not improve any more under the influence of noise,and there is a best zoom multiple,when the zoom multiple is larger than the best zoom multiple;the maximum frequency estimation error will fluctuate back and forth.The best zoom multiple curves under different signal-to-noise ratios given provide a theoretical basis for the choice of the appropriate zoom multiples of the FT continuous zoom analysis method in engineering applications. As a discrete spectrum correction method, the Fourier transform (FT) continuous zoom analysis method is widely used in vibration signal analysis, but little effort had been made on this method's anti-noise performance. It is widely believed that the analysis accuracy of the method aiming at the problem above, this paper analyzes the sources of frequency estimation error when a harmonic signal mixed with and Without noise is processed using the FT continuous zoom analysis. Accused to the characteristics that the local maximum of the zoom spectrum may be wrongly selected when the signal is corrupted with noise, the number of wrongly selected spectrum lines is deduced under different signal- to- noise ratio and local zoom multiple, and then the maximum frequency estimation error is given here. The validity of the present ed analysis is confirmed by simulations results. The frequency estimation accuracy of this method will not improve any more under the influence of noise, and there is a best zoom multiple, when the zoom multiple is larger than the best zoom multiple; the maximum frequency estimation error will fluctuate back and forth. The best zoom multiple curves under different signal-to-noise ratios given provide a theoretical basis for the choice of the appropriate zoom multiples of the FT continuous zoom analysis method in engineering applications.